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Since 1987 - Covering the Fastest Computers in the World and the People Who Run ThemTue, 26 Sep 2017 18:39:43 +0000en-UShourly1https://wordpress.org/?v=4.8.260365857Amazon Debuts New AMD-based GPU Instances for Graphics Accelerationhttps://www.hpcwire.com/2017/09/12/amazon-debuts-new-amd-based-gpu-instances-graphics-acceleration/?utm_source=rss&utm_medium=rss&utm_campaign=amazon-debuts-new-amd-based-gpu-instances-graphics-acceleration
https://www.hpcwire.com/2017/09/12/amazon-debuts-new-amd-based-gpu-instances-graphics-acceleration/#respondTue, 12 Sep 2017 22:04:17 +0000https://www.hpcwire.com/?p=39770Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The new instance is based on AMD’s FirePro S7150x2 Server GPUs equipped with AMD Multiuser GPU technology. The AWS move is a win for AMD which has been on a roll of late […]

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The new instance is based on AMD’s FirePro S7150x2 Server GPUs equipped with AMD Multiuser GPU technology. The AWS move is a win for AMD which has been on a roll of late with the launch of its EPYC chip line perhaps being the high point at least in HPC terms.

In making the announcement, AWS said the new instance type allows users to run graphics applications at a fraction of the cost of using graphics workstations, and can reduce the cost of streaming graphics applications with AppStream 2.0 by up to 50%. Achieving fast graphics performance in the cloud has long been challenging while boosting performance locally with high-end workstations is expensive.

“Graphics Design instances are ideal for delivering applications that rely on hardware acceleration of DirectX, OpenGL, or OpenCL, such as Adobe Premiere Pro, Autodesk Revit, and Siemens NX. With this launch, AppStream 2.0 now offers three graphics instance types – Graphics Design, Graphics Desktop, and Graphics Pro – optimized to support a broad selection of graphics workloads,” said AWS.

There are four Graphics Design instance sizes with different GPU and compute combinations that scale to support the performance requirements of a range of graphics applications such as engineering and creative design. The smallest instance size available “is large, with 2 vCPU, 7.5 GiB system memory, and 1 GiB graphics memory. The highest performing instance size available is 4xlarge with 16 vCPUs, 61 GiB system memory, and 8 GiB graphics memory. This range of instance sizes allows you to select the configuration that matches your application’s requirements and provide your users a fluid and high-performance experience.”

Radeon Pro virtualized GPUs feature Multi-user GPU, which AMD says is the industry’s first and only hardware-based virtualization technology in a GPU, based on SR-IOV (Single Root I/O Virtualization). SR-IOV is a big deal for three reasons, says the company:

GPU scheduling logic in hardware helps to ensure better quality of service for users

It preserves the data integrity of Virtualized Machines (VM) and their application data through hardware-enforced memory isolation logic preventing one VM from being able to access another VM’s data

It exposes all graphics functionality of the GPU to applications allowing for full virtualization support for not only graphics APIs like DirectX and OpenGL but also GPU compute APIs like OpenCL.

]]>https://www.hpcwire.com/2017/09/12/amazon-debuts-new-amd-based-gpu-instances-graphics-acceleration/feed/039770Dell Strikes Reseller Deal with Atos; Supplants SGIhttps://www.hpcwire.com/2017/08/22/dell-strikes-reseller-deal-atos-supplants-sgi/?utm_source=rss&utm_medium=rss&utm_campaign=dell-strikes-reseller-deal-atos-supplants-sgi
https://www.hpcwire.com/2017/08/22/dell-strikes-reseller-deal-atos-supplants-sgi/#respondTue, 22 Aug 2017 15:31:59 +0000https://www.hpcwire.com/?p=39058Dell EMC and Atos announced a reseller deal today in which Dell will offer Atos’ high-end 8- and 16-socket Bullion servers. Some move from Dell had been expected following Hewlett Packard Enterprise’s purchase of SGI late last year. Dell had a similar reseller deal with SGI (SGI UV 300H) dating back to July 2015. Data […]

Dell EMC and Atos announced a reseller deal today in which Dell will offer Atos’ high-end 8- and 16-socket Bullion servers. Some move from Dell had been expected following Hewlett Packard Enterprise’s purchase of SGI late last year. Dell had a similar reseller deal with SGI (SGI UV 300H) dating back to July 2015. Data analytics, of course, is an increasingly important workflow and market segment in enterprise and HPC environments.

In making the announcement, the parties noted that the “Bullion servers are certified by SAP and Oracle and complete Dell EMC’s existing portfolio of high-end advanced PowerEdge servers. Both companies will work closely together on sales and marketing activities to offer high-performance solutions in the field of big data and the Internet of Things, development of private clouds and SAP HANA solutions. The Bullion reseller agreement is a new step in the ongoing collaboration between the two companies.”

Commenting on the deal, Steve Conway, SVP of Research and HPDA Lead Analyst, Hyperion Research (formerly IDC HPC research) said, “Following HPE’s acquisition of SGI, it was inevitable that Dell would cease promoting the SGI UV as Dell’s high-end platform for SAP HANA. It’s not surprising that Dell-EMC is now casting the Atos Bullion servers in that role, because these are also very competitive high-end HANA platforms. I assume that SGI provided most of the support for SGI UV systems sold by Dell, so those customers shouldn’t be affected by this transition.”

Dell and Atos took direct aim at competitive offerings by positioning the Bullion line as “a technological alternative at lower cost for Sparc and HP-UX systems.”

Atos says Bullion servers are used by over 100 million end-users worldwide, “mainly in Europe, North America, Africa and Brazil.” The deal may offer Atos new increased leverage in the U.S. market. The Bullion line supports up to 24 TB of memory and is highly scalable. Atos also touts TCO reduction for “large data lakes and virtualized clusters reaching up to 35 percent on database consolidation projects.”

Dell’s Ravi Pendekanti, SVP, Server Solutions, is quoted in the release, “Over the last few years, Dell EMC and Atos have been working together to combine Bullion servers and Dell EMC unified storage solutions to provide our customers with a leading solution for deployment of mission-critical SAP HANA projects. Dell EMC will now be able to resell 8 to 16 sockets Bullion servers, Atos’ leading high-end server platform which is ranked as one of the most powerful in the market. The inclusion of Bullion complements Dell’s portfolio of industry leading PowerEdge servers to host the most critical workloads with outstanding performance, reliability and scalability.”

Here are the top line results as reported by STAC (Securities Technology Analysis Center). “Compared to other publicly reported systems tested with STAC-A2 to date, this Dell solution had the:

Highest space efficiency (STAC-A2.β2.HPORTFOLIO.SPACE_EFF): 1.98x the efficiency of the previously tested system with 4 x P100 GPUs (NVDA161102); 1.95x the efficiency of the previous record holder (INTC170503)

According to STAC, the STAC-A2 is the technology benchmark standard based on financial market risk analysis. “Designed by quants and technologists from some of the world’s largest banks, STAC-A2 reports the performance, scaling, quality, and resource efficiency of any technology stack that is able to handle the workload (Monte Carlo estimation of Heston-based Greeks for a path-dependent, multi-asset option with early exercise).”

SAN JOSE, Calif., July 18, 2017 — Bright Computing, a global leader in cluster and cloud infrastructure automation software, today announced a reseller agreement with AMT.

Operating in the Information Technology market since 1994, AMT provides IT professional services, infrastructure design and build, and cloud broker services based on multi-cloud providers. Additionally, AMT specializes in HPC services, implementing cloud and on-premise solutions that incorporate the latest HPC technologies and software. For HPC workloads, AMT offers code optimization services, to deliver the best value from hardware resources and to offer infrastructure savings as a whole.

Targeting the oil and gas, life sciences, and manufacturing industries, AMT chose to partner with Bright Computing to add a turnkey infrastructure management solution to its HPC portfolio, to empower its customers to deploy clusters faster and manage them more effectively.

By offering Bright technology to its customer base, the Brazil-based systems integrator intends to combine job schedulers with Bright Cluster Manager to deliver best in class HPC solutions.

Ricardo Lugão, HPC Director at AMT, commented; “We are very impressed with Bright’s technology and we believe it will make a huge difference to our customers’ HPC environments. With Bright, the management of an HPC cluster becomes very straightforward, empowering end users to administer their workloads, rather than relying on HPC experts.”

Jack Hanna, Director Alliances at Bright Computing, added; “We welcome AMT to the Bright partner community. This is an exciting company that has a lot of traction in the HPC space in Brazil, and we look forward to offering Bright technology to its customer base.”

]]>https://www.hpcwire.com/off-the-wire/bright-computing-amt-sign-partnership-agreement/feed/037839ANSYS, Saudi Aramco & KAUST Shatter Supercomputing Recordhttps://www.hpcwire.com/off-the-wire/ansys-saudi-aramco-kaust-shatter-supercomputing-record/?utm_source=rss&utm_medium=rss&utm_campaign=ansys-saudi-aramco-kaust-shatter-supercomputing-record
https://www.hpcwire.com/off-the-wire/ansys-saudi-aramco-kaust-shatter-supercomputing-record/#respondTue, 18 Jul 2017 15:22:51 +0000https://www.hpcwire.com/?post_type=off-the-wire&p=37825PITTSBURGH, July 18, 2017 — ANSYS (NASDAQ: ANSS), Saudi Aramco and King Abdullah University of Science and Technology (KAUST) have set a new supercomputing milestone by scaling ANSYS Fluent to nearly 200,000 processor cores – enabling organizations to make critical and cost-effective decisions faster and increase the overall efficiency of oil and gas production facilities. This supercomputing record represents a more than 5x increase over […]

PITTSBURGH, July 18, 2017 — ANSYS (NASDAQ: ANSS), Saudi Aramco and King Abdullah University of Science and Technology (KAUST) have set a new supercomputing milestone by scaling ANSYS Fluent to nearly 200,000 processor cores – enabling organizations to make critical and cost-effective decisions faster and increase the overall efficiency of oil and gas production facilities.

This supercomputing record represents a more than 5x increase over the record set just three years ago, when Fluent first reached the 36,000-core scaling milestone.

The calculations were run on the Shaheen II, a Cray XC40 supercomputer, hosted at the KAUST Supercomputing Core Lab (KSL). By leveraging high performance computing (HPC), ANSYS, Saudi Aramco and KSL sped up a complex simulation of a separation vessel from several weeks to an overnight run. This simulation is critical to all oil and gas production facilities – empowering organizations around the world to reduce design development time and better predict equipment performance under varying operational conditions. Saudi Aramco will apply this technology to make more-informed, timely decisions to retrofit separation vessels to optimize operation throughout an oil field’s lifetime.

“Today’s regulatory requirements and market expectations mean that manufacturers must develop products that are cleaner, safer, more efficient and more reliable,” said Wim Slagter, director of HPC and cloud alliances at ANSYS. “To reach such targets, designers and engineers must understand product performance with higher accuracy than ever before – especially for separation technologies, where an improved separation performance can immediately increase the efficiency and profitability of an oil field. The supercomputing collaboration between ANSYS, Saudi Aramco and KSL enabled enhanced insight in complex gas, water and crude-oil flows inside a separation vessel, which include liquid free-surface, phase mixing and droplets settling phenomena.”

“Our oil and gas facilities are among the largest in the world. We selected a complex representative application – a multiphase gravity separation vessel – to confirm the value of HPC in reducing turnover time, which is critical to our industry,” said Ehab Elsaadawy, computational modeling specialist and oil treatment team leader at Saudi Aramco’s Research and Development Center. “By working with strategic partner, KAUST, we can now run these complex simulations in one day instead of weeks.”

“Multiphase problems are complex and require multiple global synchronizations, making them harder to scale than single phase laminar or turbulent flow simulation. Unstructured mesh and complex geometry add further complexity,” said Jysoo Lee, director, KAUST Supercomputing Core Lab. “Our scalability tests are not just designed for the sake of obtaining scalability at scale. This was a typical Aramco separation vessel with typical operation conditions, and larger core counts are added to reduce the time to solution. ANSYS provides a viable tool for Saudi Aramco to solve their design and analysis problems at full capacity of Shaheen. And for KAUST-Aramco R&D collaboration, this is our first development work. There are more projects in the pipeline.”

About ANSYS, Inc.

If you’ve ever seen a rocket launch, flown on an airplane, driven a car, used a computer, touched a mobile device, crossed a bridge, or put on wearable technology, chances are you’ve used a product where ANSYS software played a critical role in its creation. ANSYS is the global leader in engineering simulation. We help the world’s most innovative companies deliver radically better products to their customers. By offering the best and broadest portfolio of engineering simulation software, we help them solve the most complex design challenges and create products limited only by imagination. Founded in 1970, ANSYS employs thousands of professionals, many of whom are expert M.S. and Ph.D.-level engineers in finite element analysis, computational fluid dynamics, electronics, semiconductors, embedded software and design optimization. Headquartered south of Pittsburgh, Pennsylvania, U.S.A., ANSYS has more than 75 strategic sales locations throughout the world with a network of channel partners in 40+ countries. Visit www.ansys.comfor more information.

About Saudi Aramco

Saudi Aramco is the state-owned oil company of the Kingdom of Saudi Arabia and a fully integrated global petroleum and chemicals enterprise. Over the past 80 years, we have become a world leader in hydrocarbons exploration, production, refining, distribution and marketing. Saudi Aramco’s oil and gas production infrastructure leads the industry in scale of production, operational reliability, and technical advances. Our plants and the people who run them make us the world’s largest crude oil exporter, producing roughly one in every eight barrels of the world’s oil supply.

About King Abdullah University of Science and Technology (KAUST)

KAUST advances science and technology through distinctive and collaborative research integrated with graduate education. Located on the Red Sea coast in Saudi Arabia, KAUST conducts curiosity-driven and goal-oriented research to address global challenges related to food, water, energy and the environment. Established in 2009, KAUST is a catalyst for innovation, economic development and social prosperity in Saudi Arabia and the world. The university currently educates and trains over 900 master’s and doctoral students, supported by an academic community of 150 faculty members, 400 postdocs and 300 research scientists. With 100 nationalities working and living at KAUST, the university brings together people and ideas from all over the world. www.kaust.edu.sa

The KAUST Supercomputing Core Lab mission is to inspire and enable scientific, economic and social advances through the development and application of HPC solutions, through collaboration with KAUST researchers and partners, and through the provision of world-class computational systems and services. Visit https://corelabs.kaust.edu.sa/supercomputing/ for more information.

]]>https://www.hpcwire.com/off-the-wire/ansys-saudi-aramco-kaust-shatter-supercomputing-record/feed/037825Summer Reading: IEEE Spectrum’s Chip Hall of Famehttps://www.hpcwire.com/2017/07/17/summer-reading-ieee-spectrums-chip-hall-fame/?utm_source=rss&utm_medium=rss&utm_campaign=summer-reading-ieee-spectrums-chip-hall-fame
https://www.hpcwire.com/2017/07/17/summer-reading-ieee-spectrums-chip-hall-fame/#respondMon, 17 Jul 2017 14:43:29 +0000https://www.hpcwire.com/?p=37785Take a trip down memory lane – the Mostek MK4096 4-kilobit DRAM, for instance. Perhaps processors are more to your liking. Remember the Sh-Boom processor (1988), created by Russell Fish and Chuck Moore, and named after the bar in which it was conceived. Intel, AMD, and paid big licensing fees for its scheme to run […]

Take a trip down memory lane – the Mostek MK4096 4-kilobit DRAM, for instance. Perhaps processors are more to your liking. Remember the Sh-Boom processor (1988), created by Russell Fish and Chuck Moore, and named after the bar in which it was conceived. Intel, AMD, and paid big licensing fees for its scheme to run faster than the clock on the circuit board.

Lists are often fun. Last month, the IEEE Spectrum created a Chip Hall of Fame, “To honor and tell the stories of these renowned blobs of silicon—and their creators and users.” It is by no means comprehensive, and the first class of inductees draws from the Spectrum’s “25 Microchips That Shook the World,” article which appeared in 2009 although there are many others chips as well.

As noted in the introduction to the Chip Hall of Fame, written by Stephen Cass, “[S]ome chips stand out like a celebrity on the red carpet. Many of these integrated circuits found glory by directly powering products that transformed the world, while others cast a long shadow of influence over the computing landscape. And some became cautionary tales in their failed ambitions.”

Don’t look for KNL or P100. None of the new chips on the block are present, but the Spectrum promises a growing cast of awardees annually and is seeking input on which ones are deserving. For a bit of summer whimsy, check out the lists.

Feature image: “The 6502 chip wasn’t just faster than its competitors—it was also way cheaper, selling for US $25 while Intel’s 8080 and Motorola’s 6800 were both fetching nearly $200.” Image source: Computer History Museum.

Today at its developer conference in Beijing, Baidu announced a broadening of its AI partnership with Nvidia, including plans to bring Nvidia’s recently announced 120 TFLOPS Volta GPUs to Baidu Cloud and adoption of Nvidia’s DRIVE PX platform for Baidu’s newly named “Apollo” self-driving car strategy.

Although the companies did not disclose financial details, Nvidia stock jumped nearly 4 percent within hours of the announcement of the deal, which expands the Nividia’s entre to the vast potential of the Chinese market.

In addition, Baidu said it will optimize Baidu’s open source PaddlePaddle open source deep learning framework for Volta GPUs and bring AI capabilities to the Chinese consumer market by adding Baidu’s Duer OS voice-recognition AI system to Nvidia SHIELD TV.

“We see AI transforming every industry, and our strategy is to help democratize AI everywhere, in every cloud, in every AI framework, from the datacenter to the edge to the self-driving car,” said Ian Buck, Nvidia vice president and general manager of accelerated computing, in a pre-announcement press briefing.

The availability of the Volta GPU architecture within the PaddlePaddle deep learning framework is aimed at supporting researchers and companies, along with Baidu, develop AI applications for search rankings, image classification services, real-time speech understanding, visual character recognition and other AI-powered services.

In announcing its selection of Nvidia’s DRIVE PX 2 AI supercomputer for its open source Apollo autonomous vehicle platform, Baidu said Apollo will also incorporate Tesla GPUs along with Nvidia CUDA and TensorRT software, adding that the self-driving car that Baidu showed recently at CES Asia was powered by DRIVE PX 2.

Several Chinese automakers today announced that they will join the Eco Partner Alliance of Apollo, including Changan, Chery Automobile, FAW, and Greatwall Motor.

In the Chinese AI home market, Baidu Duer OS, the company’s conversational AI system, will provide voice command capabilities to NVIDIA’s SHIELD TV for streaming video, gaming and smart home assistance. A version of the streamer, with custom software made for China, will be available later this year.

“NVIDIA and Baidu have pioneered significant advances in deep learning and AI,” said Buck. “We believe AI is the most powerful technology force of our time, with the potential to revolutionize every industry. Our collaboration aligns our exceptional technical resources to create AI computing platforms for all developers – from academic research, startups creating breakthrough AI applications, and autonomous vehicles.”

Editor’s note: This article first appeared in HPCwire’s sister publication EnterpriseTech.

]]>https://www.hpcwire.com/2017/07/05/nvidia-baidu-expand-ai-partnership/feed/037438AMD Charges Back into the Datacenter and HPC Workflows with EPYC Processorhttps://www.hpcwire.com/2017/06/20/amd-charges-back-data-center-hpc-workflows-epyc-processor/?utm_source=rss&utm_medium=rss&utm_campaign=amd-charges-back-data-center-hpc-workflows-epyc-processor
https://www.hpcwire.com/2017/06/20/amd-charges-back-data-center-hpc-workflows-epyc-processor/#respondTue, 20 Jun 2017 22:23:02 +0000https://www.hpcwire.com/?p=36877AMD is charging back into the enterprise datacenter and select HPC workflows with its new EPYC 7000 processor line, code-named Naples, announced today at a “global” launch event in Austin TX. In many ways it was a full frontal assault on Intel’s dominance in the x86 datacenter landscape. Claiming performance and cost advantages and supported […]

AMD is charging back into the enterprise datacenter and select HPC workflows with its new EPYC 7000 processor line, code-named Naples, announced today at a “global” launch event in Austin TX. In many ways it was a full frontal assault on Intel’s dominance in the x86 datacenter landscape. Claiming performance and cost advantages and supported by statements from key OEMs, ODMs, and hyperscalers – HPE, Dell, and Microsoft Azure for example – AMD is hoping to convince HPC and datacenter customers it is back for the long haul.

Aware there may be market reluctance after its absence from the datacenter, Scott Aylor, AMD corporate VP and GM of enterprise solutions business, said “It’s not enough to come back with one product, you’ve got to come back with a product cadence that moves as the market moves. So not only are we coming back with EPYC, we’re also [discussing follow-on products] so when customers move with us today on EPYC they know they have a safe home and a migration path with Rome.” AMD has committed to socket compatibility between EPYC 7000 line and Rome, code name of the next scheduled generation AMD processor aimed at the datacenter.

AMD showcased some gaudy performance and price-performance benchmarks comparing EPYC to Broadwell line. In a pre-launch briefing with HPCwire, Aylor said, “These numbers are very big, so they show very measurable separation from what is available with Broadwell. Part of that is quite frankly because we didn’t design EPYC to compete with Broadwell. We designed it to compete with what’s coming. When [Intel’s] Skylake comes later this summer, we think these comparisons will still be very strong against the platinum, gold silver and bronze of Skylake.”

Based on the Zen core, EPYC is a line of system on a chip (SoC) devices designed with enhanced memory bandwidth and fast interconnect in mind. AMD also introduced a one-socket device, optimized for many workloads, which AMD says will invigorate a viable one-socket server market. With EPYC, “we can build a no compromise one-socket offering that will allow us to cover up to 50 percent of the two-socket market that is today held by the [Intel Broadwell] E5-2650 and below,” said Aylor.

AMD clearly has big ambitions. Earlier this spring it introduced Ryzen7 processor line, also based on the Zen core, and targeting high performance gaming. EPYC is aimed squarely at the datacenter. Aylor briefed HPCwire on EPYC before the launch and some of the technical details were still not available. It is an SoC product stack with a range of offerings roughly mimicking the Broadwell product stack. EPYC has up to 32 cores and 8 DDR4 channels per CPU allowing it to address 2TB of memory. The I/O is 128 PCIe lanes.

“The SoC approach we have taken allows all of the IO that has historically lived on an external bridge or IO hub to be fully integrated that into the device,” said Aylor. One result is low latency high performance connections. The PCIe lanes are configurable, “so you can use them to connect to SATA links, directly connect to NVMe links. It also facilitates a strong connection to high performance GPUs.” AMD plans to show an EPYC plus Radeon Instinct GPU machine learning platform at its conference this week.”

AMD presented both SPECint (integer) and SPECfp (floating point) performance comparisons with the Broadwell as well as price point comparisons (how much performance the same number of dollars will be of each processor) some of which are shown below.

“We’re tiering products in 32, 24, and 16-core ranges,” said AYLOR. The idea, of course, is satisfy widely varying needs. The top end aimed at scale out and HPC workloads, he said. The bottom tier allows users to closely manage per core licensing costs. “We have tried to cover the vast majority of the market that exists today in the Broadwell family,” says Aylor. Every product will have a dedicated security processor.

“Sometime people will say benchmarks are interesting but how do you do in the real world. Well we will showcase a fluid dynamics HPC workload, Apache/Spark, and software defined storage reference architecture [at the launch]. We will also have an open stack cloud based implementation,” said Aylor. AMD was expecting on the order 600 attendees for the EPYC launch.

Moving back into the datacenter is a huge bet by AMD that’s required a very substantial investment in the Zen core and EPYC. Seeking to buttress the gamble, AMD has seemingly got buy-in from several market makers and many ecosystem partners. Here are four endorsements included in the official release; while the statements are on the over enthusiastic side they nonetheless suggest AMD has done productive groundwork with partners:

HPE. “The EPYC processor represents a paradigm shift in computing and will usher in a new era for the IT ecosystem,” said Antonio Neri, EVP and general manager Enterprise Group, HPE. “Starting with the Cloudline CL3150 and expanding into other product lines later this year, the arrival of EPYC in HPE systems will be welcomed by customers who are eager to deploy the performance and innovation EPYC delivers.”

Dell EMC. “As an industry leader, we are committed to driving IT Transformation for our customers,” said Ashley Gorakhpurwalla, president, server solutions division at Dell EMC, “Our next generation of PowerEdge servers are the bedrock of the modern datacenter that are designed to maximize business scalability and intelligent automation with integrated security. The combination of PowerEdge and the AMD EPYC performance and security capabilities will create unique compute solutions for our customers to accelerate workloads and protect their business.”

Baidu. “As the world’s largest Chinese language search engine and leading AI-Tech company, Baidu prides itself on simplifying a complex world through technology,” said By Dr. Zhang Ya Qin, president of Baidu. “The AMD EPYC processor powered one-socket server can significantly increase our datacenter computing efficiency, reduce TCO and lower energy consumption. We will start deploying with the launch of AMD EPYC and I look forward to our cooperation leading to scaled EPYC adoption this year, and ongoing innovations.”

Microsoft. “We’ve worked to make Microsoft Azure a powerful enterprise grade cloud platform, that helps guide the success of our customers, no matter their size or geography,” said Girish Bablani, corporate vice president, Azure Compute, Microsoft Corp. “To power Azure, we require the most cutting-edge infrastructure and the latest advances in silicon which is why we intend to be the first global cloud provider to deliver AMD EPYC, and its combination of high performance and value, to customers.”

The single socket gambit is another interesting aspect to AMD’s initiative. Currently two socket servers rule the roost.

Here’s the AMD pitch: “In our one socket offering we have come up with a clever way to maintain all of the I/O capabilities that you would get in a two socket as well as the full complement of eight memory channels. Today people buy two socket, sometimes because they need to, but more often than not because they have to. There are many examples in which I/O rich [workloads] like storage, like GPU compute, and some vertical workloads where people don’t necessarily need two sockets from a CPU performance perspective,” said Aylor.

AMD’s single socket offering cuts costs substantially, according to Aylor. “We’ve selectively optimized a couple of skews for one socket only. So these are skews that are one socket capable only,” said Aylor. As an example of how the one socket and two socket offerings are distinguished, he cited on package interconnect, “The infinity fabric that would normally connect the two sockets in a two socket system, we repurpose that interconnect into more I/O lanes and that’s how you have in a two socket solution 128 lanes of PCIe and in a one socket solution you still keep the same level of connectivity.”

AMD has singled out a number of vertical as good fits for one socket EPYC servers. Perhaps not surprisingly, storage is one. “Not only base line storage but software defined storage with EPYC’s ability to attach a massive number of SATA drives to a one socket. We also see a strong opportunity in certain areas of high performance computing, especially those that tend to focus on memory bound application. And we have an oil and gas reservoir simulation demo,” said Aylor.

]]>https://www.hpcwire.com/2017/06/20/amd-charges-back-data-center-hpc-workflows-epyc-processor/feed/036877ISC 2017 Student Day Tackles the Worldwide HPC Workforce Shortagehttps://www.hpcwire.com/2017/06/12/isc-2017-student-day-tackles-worldwide-hpc-workforce-shortage/?utm_source=rss&utm_medium=rss&utm_campaign=isc-2017-student-day-tackles-worldwide-hpc-workforce-shortage
https://www.hpcwire.com/2017/06/12/isc-2017-student-day-tackles-worldwide-hpc-workforce-shortage/#respondMon, 12 Jun 2017 16:12:02 +0000https://www.hpcwire.com/?p=36411At a time when university graduates in science and engineering may find job markets difficult, thousands of well-paying jobs go unfilled across the world because the graduates lack basic HPC competency and because supercomputing is sometimes mistakenly seen as an old technology. As part of the new STEM Student Day at the ISC17 conference (Wednesday, […]

At a time when university graduates in science and engineering may find job markets difficult, thousands of well-paying jobs go unfilled across the world because the graduates lack basic HPC competency and because supercomputing is sometimes mistakenly seen as an old technology. As part of the new STEM Student Day at the ISC17 conference (Wednesday, June 21), Michael Bader of the Technical University of Munich (TUM) and I will attempt to describe the problem and the opportunities.

This issue has been near and dear to me for quite a while. It affects the futures of young people coming out of universities, and to the extent that it’s not addressed, it will constrain the future of the global HPC industry. I invited Dr. Bader to team with me because TUM is a global leader in responding to this issue on behalf of its students.

The ProblemThe HPC personnel shortage is no accident. When HPC funding from the U.S. Government and allied nations declined sharply after the end of the Cold War, the HPC market entered a period of slowdown from which it did not start to recover until about the year 2002, when the fast rise of HPC clusters caused a five-year spurt of 20% annual revenue growth. Between 2000 and 2016, the HPC market doubled in size, from about $11 billion to $22.4 billion—creating the need for many new employees in the process.

Steve Conway, Hyperion SVP

The period of HPC slowdown, occurring as it did alongside the explosive growth of Internet companies, helped to transform the image of HPC into that of a maturing and even a dying, “old technology” market. The number of university programs in computational science and related fields plummeted, as did HPC-related internship and postgraduate fellowship opportunities. Young people who might have chosen an HPC career a decade earlier all too often opted instead for employment with “new technology” Internet, PC or gaming companies. As a result, a high proportion of today’s graying HPC workforce is within a decade of retirement age and educational institutions are not producing enough HPC-trained graduates to replace them.

Worldwide StudyAn extensive study we conducted for the U.S. Department of Energy in 2010—subsequent studies confirm that the situation hasn’t changed much since then—confirmed that the HPC community has only begun to address this job candidate shortage through new curricular and internship offerings, as well as through accelerated on-the-job training, but there is still a long way to go – especially in view of the challenges needed to harness the potential of exascale computers.

The important future inflection points for the study respondents from HPC sites fell into the categories of: parallelism, petascale/exascale computing, HPC system heterogeneity, HPC system architectural balance, HPC system reliability, and HPC system and data center power and cooling. These inflection points are closely related to each other and therefore represent a complex of issues that in most cases cannot be addressed entirely alone.

Nearly all (93%) of the HPC centers said it is “somewhat hard” or “very hard” to hire staff with the requisite skills. It is especially telling that the majority of the centers (56%) fell into the “very hard” category.

The most fruitful source of qualified candidates for HPC positions are “university graduates in mathematics, engineering, or the physical sciences” (cited by 63% of the respondents). A smaller but substantial percentage of the respondents (48%) pointed to “university graduates in computer science.”

Many Universities Are in a BindThe single biggest recommendation offered by HPC-knowledgeable study respondents in academic and training organizations was for universities to expand coursework in computational science, and to integrate computational science methods into the requirements for science and engineering degrees, certainly at the graduate level and preferably also at the undergraduate level.

If simulation really has become the third branch of the scientific method, complementing theory and physical experimentation, it stands to reason that science and engineering majors should be required to attain basic competency in computer simulation. But for many universities, that’s far easier said than done. Science and engineering curricula often are so tightly packed with requirements that adding anything new is a herculean task.

Yet, for the sake of graduating students and HPC’s growing importance in our societies, innovative solutions to this education problem need to be found. Michael Bader will present TUM’s approach at ISC. There are other universities pursuing innovative approaches. Hyperion plans to continue tracking this issue closely.

Description of ISC2017 STEM STUDENT DAY & GALA (from ISC web site)

ISC High Performance is a forum for HPC community members to network and explore opportunities – for current experts but also for future generations. We have created a program to welcome STEM students into the world of high performance computing, demonstrate how technical skills can propel their future careers in this area, introduce them to the current job landscape, and also show them what the European HPC workforce will look like in 2020 and beyond.

The ISC STEM Student Day & Gala will take place on Wednesday, June 21 and is free for students.

Author Bio:Steve Conway, Senior Research Vice President, Hyperion Research, directs research related to the worldwide HPC and high performance data analysis (HPDA) markets. He is a member of the steering committee of the HPC User Forum and a frequent conference speaker and author, including of the global study for the U.S. Department of Energy, Talent and Skill Sets Issues Impacting HPC Data Centers. Mr. Conway was an executive at Cray, SGI and CompuServe. He had a 12-year career in university teaching and administration at Boston University and Harvard University. A former Senior Fulbright Fellow, he holds advanced degrees in German from Columbia University and in comparative literature from Brandeis University.

]]>https://www.hpcwire.com/2017/06/12/isc-2017-student-day-tackles-worldwide-hpc-workforce-shortage/feed/036411Doug Kothe on the Race to Build Exascale Applicationshttps://www.hpcwire.com/2017/05/29/doug-kothe-race-build-exascale-applications/?utm_source=rss&utm_medium=rss&utm_campaign=doug-kothe-race-build-exascale-applications
https://www.hpcwire.com/2017/05/29/doug-kothe-race-build-exascale-applications/#respondMon, 29 May 2017 19:00:55 +0000https://www.hpcwire.com/?p=36046Ensuring there are applications ready to churn out useful science when the first U.S. exascale computers arrive in the 2021-2023 timeframe is Doug Kothe’s job. No pressure. He’s not alone, of course. The U.S. Exascale Computing Project (ECP) is a complicated effort with many interrelated parts and contributors, all necessary for success. Yet Kothe’s job […]

Ensuring there are applications ready to churn out useful science when the first U.S. exascale computers arrive in the 2021-2023 timeframe is Doug Kothe’s job. No pressure. He’s not alone, of course. The U.S. Exascale Computing Project (ECP) is a complicated effort with many interrelated parts and contributors, all necessary for success. Yet Kothe’s job as director of application development is one of the more visible and daunting and perhaps best described by his boss, Paul Messina, ECP director.

“We think of 50 times [current] performance on applications [as the exascale measure of merit], unfortunately there’s a kink in this,” said Messina. “The kink is people won’t be running today’s jobs in these exascale systems. We want exascale systems to do things we can’t do today and we need to figure out a way to quantify that. In some cases it will be relatively easy – just achieving much greater resolutions – but in many cases it will be enabling additional physics to more faithfully represent the phenomena. We want to focus on measuring every capable exascale system based on full applications tackling real problems compared to what they can do today.”

Doug Kothe, ECP

In this wide-ranging discussion with HPCwire, Kothe touches on ECP application development goals and processes; several technical issues such as efforts to combine data analytics with mod/sim and the need for expanded software frameworks to accommodate exascale applications; and early thoughts for incorporating neuromorphic and quantum computing not currently part of the formal ECP plan. Interestingly, his biggest worry isn’t reaching the goal on schedule – he believes the application teams will get there – but post-ECP staff retention when industry comes calling.

By way of review, ECP is a collaborative effort of two Department of Energy organizations—the Office of Science and the National Nuclear Security Administration. Six applications areas have been singled out: national security; energy security, economic security, scientific discovery; earth science; and health care. In terms of app-dev, that’s translated into 21 Science & Energy application projects, 3 NNSA application projects, and 1 DOE / NIH application project (precision medicine for cancer).

It’s not yet clear what the just released FY2018 U.S. Budget proposed by the Trump Administration portends. Funding for science programs were cut nearly across the board although ECP escaped. Kothe says simply, “It is the beginning of the process for the FY18 budget, and while the overall budget is determined, we will continue working on the applications that are already part of the ECP.”

In keeping with ECP’s broad ambitions, Kothe says, “All of our applications teams are focused on very specific challenge problems and by our definition a challenge problem is one that is intractable today, needs exascale resources, and is a strategic high priority for one of the DOE program offices. We aren’t claiming we are going to solve all the problems but we are claiming is simulation technology that can address the problem. The point is we have the applications vectored in rather specific directions.” (Summary list below, click to enlarge)

RISE OF DATA ANALYTICSOne of the more exciting and new-to-HPC areas is incorporation of data analytics into the HPC environment overall and ECP in particular. Indeed, harmonizing or at least integrating the big data and modelling and simulation is a goal specified by the National Strategic Computing Initiative. Data-driven science isn’t new nor is researcher familiarity with underlying statistics. But the sudden rise machine/deep learning techniques and including many that rely on lower precision calculations is somewhat new to the scientific computing community and an area where the commercial world has perhaps taken the lead. Kothe labels the topic “white hot”.

“Not being trained in the data analytics area I’ve been doing a lot of reading and talking [to others]. A large fraction of the area I feel like I know, but I didn’t appreciate the other 20 or 30 percent. The point is by exposing our applications teams to the data analytics community, even just calling libraries, we are going to see some interesting in situ and computational steering use cases. As an example of in situ, think of turbulence. It could be an LES (large eddy simulation) whose parameters could have been tuned a priori by machine learning or chosen on the fly by machine learning. That kind of work is already going on at some universities,” Kothe says.

Climate modeling is a case point. “A big challenge is subgrid models for clouds. Right now and even at exascale we probably cannot do one km or less resolution everywhere. We may be able to do regional coupled simulations that way, but if we try to do five or ten kilometers everywhere – of course it will vary whether over ocean or land ice, sea ice, or atmosphere – you will still have many clouds lost in one cell. You need a subgrid model. Maybe machine learning could be used to select the parameters. Think of a bunch of little LES models running in a 10km x10km cell holding lots of clouds that are then scaled into the higher level physics. I think subgrid models are potentially a poster child for machine learning.”

Steering simulations is another emerging use case. “There’s a couple of labs, Lawrence Livermore in particular, that are already using machine learning to make decisions, to automate decisions about mesh quality for fluid and structure simulations where the mesh is just flowing with the moving material and the mesh may start to contort in a way that will cause the numerical solution to break down or errors to increase. You could do quality checks on the fly and correct the mesh with machine learning.”

One interesting use is being explored as part of the Exascale CANcer Distributed Learning Environment (CANDLE) project (see HPCwire article, Enlisting Deep Learning in the War on Cancer). Part of the project is clarifying the RAS (gene) network activity. The RAS network is implicated very many cancers. “You have machine learning orchestrating ensembles of molecular dynamics simulations [looking at docking scenarios with the RAS protein] and examining factors that are involved in docking,” says Kothe. Machine learning can recognize already known areas and reduce need for computationally intensive simulation in those areas while zeroing in on lesser known areas for intense quantum chemistry simulations. Think of it as zooming in and out as needed.

FRAMEWORKS REVISITEDClearly there’s no shortage of challenges for ECP application development. Kothe cites optimizing node performance and memory management among the especially thorny ones, “We’ve now have many levels of memory exposed to us. We don’t really quite know how best to use it.” Data structure choices can also be problematic and Kothe suggests frameworks may undergo a revival,

One of the application teams (astrophysics), recalls Kothe, came to him and said, “I am afraid to make a choice for a data structure that would be pervasive in my whole code because it might be the wrong one and I’m stuck with it.'” The point is I think what we are seeing with the applications a kind of ‘going back to the future’ in late 80s when you saw lots of heavyweight frameworks where an application would call out to a black box and say register this array for me and hand me back the pointer.

“That’s good and it’s bad. The bad part is you’re losing control and now you have to schlep around this black box and you don’t know if it is going to do what you want it to do. The good part is if you are on a KNL system or an NVIDIA system, you are on different nodes, and that block box memory manager would have been tuned for that hardware. [In] dealing with memory hierarchy risks, I think we are probably seeing applications move more towards frameworks which I find think is a good idea. We’ve learned kind of what I call the big F or little f frameworks. I think we’re learning how to balance the two so applications can be portable and not have to rely on an army of people but still do something that’s more agile than just choose one data structure and hope it works.”

Performance portability is naturally a major consideration. Historically, says Kothe, application developers and he includes himself in the category, “We chose portability over performance because we want to make sure our science can be done anywhere. Performance can’t be an afterthought but it often is. Portability in my mind has several dimensions. So the new system shows up and it is probably not something out of left field, you know something about it, but what’s a reasonable amount of effort that you think should be required to port your code? How much of the code base do you think should change? What is correctness in terms of the problem and getting the answer.

“I would claim that a 64-bit comparison is probably not realistic. I mean it’s probably not even appropriate. What set of problems would you run? You need to run real problems. We’re asking each app team to define what they think portability means and hope that collectively we’ll move towards a good definition and a good target for all the apps but I think it will end up being fairly app specific.”

THE CO-DESIGN IMPERATIVEThe necessity of co-design has become a given throughout HPC as well as with the ECP. Advancing hardware and new systems architectures must be taken into account not merely to push application performance but to get them to run at all. However coupling software too tightly to a specific machine or architecture is limiting. Currently ECP has established six co-design centers to help deal with specific challenges. Kothe believes use of motifs may help.

“Every application team at some level will be doing some vertically integrated co-design and there is probably more software co-design going on – the interplay with the compilers and runtime systems and that kind of thing – than anything else. By having the co-design centers identify a small number of motifs that applications are using, I think we can leverage a deep dive co-design on the motifs as opposed to doing kind of an extensive co-design vertically integrated within every application. This is new and there are some risks. But long term, my dream would be we [develop] community libraries that are co-designed around motifs that are used broadly among the applications.

“The poster child is probably [handling] particles. Almost every application has a discrete particle model for something and that’s good and it’s a challenge. So how do you encapsulate the particle [model] in a way that it can be co-designed not as a separate activity that’s not thinking about the [specific] consumer of that motif, but just thinking about making that motif rock and roll. That’s the challenge, to co-design motifs so they can be broadly used and I have high hopes there.”

STAY ON TARGET“A big challenge with application developers, is everything sounds cool and looks good, so we want to keep them focused. Year by year the applications have laid out a number of milestones and for the most parts the milestones are step by step progression towards that challenge program. The progression has many dimensions: is the science capability improving, better physics, better algorithms; is the team utilizing the hardware efficiently [such as] state of the art test beds, the latest systems on the floor; are they integrating software technologies and probably one of the most important is they are using co-design efforts,” says Kothe

One ECP-wide tool is a comprehensive project database where “all the R&D projects and applications and software technology, all their plans and milestones are in one place.” A key aspect of ECP, says Kothe, is that everyone can see what everyone else is doing and how they are progressing.

Think of a milestone as a handful of things, says Kothe, that are generally tangible such as software release or a demonstration simulation. “It could be a report or a presentation. It can even be a small write up that says I tried this algorithm and it didn’t work. A milestone is a decision point.

“It’s not always a huge success. Failure can be just as valuable. Sometimes we can force a sense of urgency. We can review this seven-year plan and say, alright you can’t bring in a technology that doesn’t have a line of sight in this timeframe, or you’ve got algorithm A and B going along [and] at this point you have make a decision and choose one and go with it. I like that. I think it imparts a sense of urgency,” Kothe.

Kothe, of course, has his own milestones. One is an annual application assessment report due every September.

“I am hearing I am a slave driver and I didn’t really think had that personality,” says Kothe. One area where he is inflexible is on scheduled releases. “We want you to release on the scheduled date, that date is gospel. What’s in the release may float. So the team and budget, we like to be pretty rigid, but what’s in the release floats based on what you have learned. You have this bag of tasks and try to get as many tasks done as you can but you still must have the release.”

SOFTWARE TECHNOLOGY SHARINGNot surprisingly, close collaboration with the software technology team is emphasized. “Right now what we have this incredible opportunity because applications teams are exposed to a lot of software technologies they’ve never seen or heard of.” It’s a bit like kids in a candy store says Kothe, “They are looking at this technology and saying I want to do that, to do that, to do that, and so the challenge for integration is on managing the interfaces and doing it in a scalable way.”

There a couple of technology projects that everyone wants to integrate, he says, and that’s big bandwidth worry when you have 20-plus application projects lined up saying “let me try your stuff because chances are there will be new APIs and new functionalities and bugs and features [too]. The software technology people are saying, ‘Doug be careful. let’s come up with a scalable process.’” Conversely, says Kothe, it is also true there’s a fair amount of great “software technology the application teams are not exploring which they should be.”

“We have defined a number of integration milestones which are basically milestones that require deliverables from two or three areas. We call that shared fate. [I know] it sounds like we are jumping off a cliff together. A good example is an application project looks at a linear solver and says ‘you don’t have the functionality I need, lets negotiate requirements.’ So the solver negotiates a new API, a new functionality, and the application team will have a milestone that says it will have integrated and tested and the new technology [by a given date] and the software technology team has to have its release say two or three months before. These things tend to be daisy chained like that. You have a release, then an integration assessment, and we might have another release to basically deal with any issues.

“Right now, early on in ECP, we’re having a lot of point-to-point interaction where there’s lots of aps that want to do lots of same or different things with lots of software projects. I think once we settle down on the requirements the software technologies will be kind of one to all [having] settled on a base functionality and a base API. An obvious example is MPI but even with MPI there’s new features and functionalities that certain aspects. We can’t take it for granted that some of these tremendous technologies like MPI are going to be there working the way we need for exascale,” says Kothe.

ECP FUTURE WATCHEven as ECP pushes forward it remains rooted in CMOS technology yet there are several newer technologies – not least neuromorphic and quantum computing – which have made great strides recently and seem on the cusp of practical application.

“One of the things I have been thinking about is even if we don’t have access to a neuromorphic chip what is its behavior like from a hardware simulator point of view. The same thing with quantum computing. Our mindset has to change with regards to the algorithms we lay out for neuromorphic or quantum. The applications teams need to start thinking about different types of algorithms. As Paul [Messina] has pointed out it’s possible quantum computing could fairly soon become an accelerator on traditional node. Making sure applications are compartmentalized is important to make that possible. It would allow us to be more flexible and extensible and perhaps exploit something like a quantum accelerator.”

Looking ahead, says Kothe, he worries most about the unknown unknowns – there will be surprises. “I feel like right now in apps space we kind of have known unknowns and we’ll hit some unknown unknowns, but I believe we are going to have a number of applications ready to go. We’ll have trips along the way and we may not do some things we plan now. I think we have an aggressive but not naive set of metrics. It’s really the people. We have some unbelievable people,” he says.

One can understand today’s attraction. Kothe points out this is likely to be a once-in-a-career opportunity and the mix of experience among the application team members significant. “What we see is millennials sitting at the table showing people new ways of doing software with gray-haired guys like me who have been to the school of hard knocks. There’s a tremendous cross fertilization. I’m confident. I saw it when we selected these teams. We had teams with rosters that looked like the all star team, but I am worried about retention. We are training people to be some of the best, especially the early career folks, so I am worried that they will be in high demand, very marketable.”

Kothe Bio from ECP website:Douglas B. Kothe (Doug) has over three decades of experience in conducting and leading applied R&D in computational applications designed to simulate complex physical phenomena in the energy, defense, and manufacturing sectors. Kothe is currently the Deputy Associate Laboratory Director of the Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL). Prior positions for Kothe at ORNL, where he has been since 2006, were Director of the Consortium for Advanced Simulation of Light Water Reactors, DOE’s first Energy Innovation Hub (2010-2015), and Director of Science at the National Center for Computational Sciences (2006-2010).

Feature Caption:The Transforming Additive Manufacturing through Exascale Simulation project (ExaAM) is building a new multi-physics modeling and simulation platform for 3D printing of metals to provide an up-front assessment of the manufacturability and performance of additively manufactured parts. Pictured: simulation of laser melting of metal powder in a 3D printing process (LLNL) and a fully functional lightweight robotic hand (ORNL).